qsar驱动的数字催化剂模型:聚烯烃弹性体的高通量设计

IF 6.5 1区 化学 Q2 CHEMISTRY, PHYSICAL
Bing Yan, Shijia Wang, Xiao Gui, Xinpeng Xing, Qishun Guo, Chengang Cao, Jian Li, Tao Jiang
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引用次数: 0

摘要

茂金属催化剂是实现乙烯/1-辛烯高温溶液聚合生产聚烯烃弹性体的关键。其中,桥接茂金属催化剂由于其优异的热稳定性和高催化活性而具有特别的商业价值。然而,它们多样而复杂的结构特征给催化剂的精确可控设计和合成带来了重大挑战,这些催化剂同时具有高活性、优异的共聚性能和生产高分子量聚合物的能力。本文采用实验和密度泛函相结合的方法研究了c1对称桥接茂金属催化剂的定量构效关系(qsar)。与大多数只关注催化剂结构的研究相反,我们的研究结果强调了基于反应过程中形成的过渡态物种来分析催化剂性能的重要性。其中,[Cp(R1)Ind(R2)2Si(R)2M(iBu)]+中乙烯π配合物的∠Cp - m−CFlu和∠M-Cα-Hα是影响催化活性的重要因素。此外,发现[Cp(R1)Ind(R2)2Si(R)2MC4H8(iBu)+…C2H4]‡中M-Cα键的长度影响共聚性能,而[Cp(R1)Ind(R2)2Si(R)2MC2H4(iBu)+…C2H4]‡中Cα-M−C1−C2的扭转角直接影响聚合产物的分子量。通过机器学习和实验验证进一步验证了这些QSARs。在此基础上,设计并合成了一种新型的高性能催化剂。最后,利用获得的QSARs,开发了具有高通量筛选能力的普遍适用的数字催化剂模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

QSAR-driven digital catalyst models: high-throughput design of polyolefin elastomers

QSAR-driven digital catalyst models: high-throughput design of polyolefin elastomers

QSAR-driven digital catalyst models: high-throughput design of polyolefin elastomers
Metallocene catalysts are pivotal in enabling the high-temperature solution polymerization of ethylene/1-octene to produce polyolefin elastomers. Among these, bridged metallocene catalysts are particularly valuable commercially owing to their exceptional thermal stability and high catalytic activity. However, their diverse and complex structural characteristics pose major challenges in the precise and controllable design and synthesis of catalysts that simultaneously exhibit high activity, superior copolymerization performance, and the ability to produce high-molecular-weight polymers. Herein, the quantitative structure–activity relationships (QSARs) of C1-symmetric bridged metallocene catalysts for ethylene/1-octene copolymerization were investigated through a combined experimental and density functional theory approach. In contrast to most studies that focus solely on the catalyst structure, our findings emphasize the importance of analyzing catalyst performance based on the transition state species formed during the reaction. Specifically, the ∠CCp–M−CFlu and the ∠M–Cα–Hα of ethylene π-complexes in [Cp(R1)Ind(R2)2Si(R)2M(iBu)]+ were identified as important influencing factor of catalytic activity. Additionally, the M–Cα bond length in [Cp(R1)Ind(R2)2Si(R)2MC4H8(iBu)+…C2H4] was found to influence copolymerization performance, while the Cα–M−C1−C2 twist angle in [Cp(R1)Ind(R2)2Si(R)2MC2H4(iBu)+…C2H4] directly affected the molecular weight of the polymerization product. These QSARs were further validated through machine learning and experimental verification. Based on these insights, a novel high-performance catalyst was designed and synthesized. Finally, a universally applicable digital catalyst model with high-throughput screening capabilities was developed, leveraging the obtained QSARs.
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来源期刊
Journal of Catalysis
Journal of Catalysis 工程技术-工程:化工
CiteScore
12.30
自引率
5.50%
发文量
447
审稿时长
31 days
期刊介绍: The Journal of Catalysis publishes scholarly articles on both heterogeneous and homogeneous catalysis, covering a wide range of chemical transformations. These include various types of catalysis, such as those mediated by photons, plasmons, and electrons. The focus of the studies is to understand the relationship between catalytic function and the underlying chemical properties of surfaces and metal complexes. The articles in the journal offer innovative concepts and explore the synthesis and kinetics of inorganic solids and homogeneous complexes. Furthermore, they discuss spectroscopic techniques for characterizing catalysts, investigate the interaction of probes and reacting species with catalysts, and employ theoretical methods. The research presented in the journal should have direct relevance to the field of catalytic processes, addressing either fundamental aspects or applications of catalysis.
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